A total of 168 macro-zooplankton samples from 42 stations in the central South China Sea （12° ～20° N, 111°～118°E, an area of about 64 × 10^4 km^2 ） were collected in September 1983 （autum...A total of 168 macro-zooplankton samples from 42 stations in the central South China Sea （12° ～20° N, 111°～118°E, an area of about 64 × 10^4 km^2 ） were collected in September 1983 （autumn） , April 1984 （spring） , August 1984 （summer） and December 1984 （winter）. Twenty-three species and subspecies of tunicates were found, of which Thalia democratica complex （including T. d. orientalis and T. d. echinata） and Doliolum denticulatum were the dominant species, and accounted for 95.7% , 90. 0%, 91.8% and 90. 5% of the total tunicates found in autumn, winter, spring and summer, respectively. The highest abundance （with a mean of 2.37 ind./m^3 ） occurred in autumn. There are strong correlations between the abundances of the tunicates and those of phytoplankton and chlorophyll a concentration. However, tunicates also aggregate in areas with low primary production in the autumn survey, probably due to the water circulation pattern.展开更多
In this paper, the distribution patterns and abundance of pelagic tunicates in the North Yellow Sea of China during the period 2006-2007 were analyzed. Zooplankton samples were obtained with vertical towing from botto...In this paper, the distribution patterns and abundance of pelagic tunicates in the North Yellow Sea of China during the period 2006-2007 were analyzed. Zooplankton samples were obtained with vertical towing from bottom to surface using a WP2 plankton net(200 μm mesh size; mouth area: 0.25 m2). Five species belonging to two classes were identified: Oikopleura dioica, O. longicauda and Fritillaria borealis belonging to class Appendicularia; Salpa fusiformis and Doliolum denticulatum of class Thaliacea. O. dioica and O. longicauda were the dominant species, occurring in the samples of all four seasons, with different distribution patterns. Their maximum abundance were 1664.7 ind. m-3(spring) and 1031.7 ind. m-3(spring) respectively. Following Oikopleura spp. were D. denticulatum, which was found only in autumn with an average abundance of 149.6 ind. m-3, and S. fusiformis, which was detected all the year long except for autumn with low abundance(max. abundance 289.4 ind. m-3 in summer). Only a very small amount of F. borealis was detected in summer samples, with an average abundance of 2.7 ind. m-3. The relationship between tunicates abundances and the environmental factors was analyzed using the stepwise regression model for each species. The variation of appendicularian abundance showed a significant correlation with the surface water temperature and with the concentration of Chl-a. No relationship was found between tunicates abundance and salinity, likely due to the slight changes in surface salinity of the studied area during the four seasons. Salps abundance and that of doliolids were significantly correlated to bottom water temperature, indicating that these two species(S. fusiformis and D. denticulatum) migrate vertically in the water column. In particular D. denticulatum, known to be a warm water species, showed not only an important correlation with water temperature, but also a spatial distribution connected to the warm currents in the North Yellow Sea. The occurrence of D. denticulatum represents an interesting result never found in past research work. Water temperature, algal distribution and currents were the most relevant environmental factors influencing the tunicate abundance and distribution in the North Yellow Sea. Further research is needed in order to get more information on the ecology of these organisms and to better understand their role in the ecosystem including the oceanic food web.展开更多
Conductive papers made from graphene and its derivatives are important for the development of electronic devices; however, elastomer-based matrices usually make it difficult for the conductive sheets to form...Conductive papers made from graphene and its derivatives are important for the development of electronic devices; however, elastomer-based matrices usually make it difficult for the conductive sheets to form continuous conductive networks. In this work, we used tunicate-derived cellulose nanocrystals （TCNC） instead of traditional elastomers as the matrix for polydopamine （PDA）-coated and reduced graphene oxide （GO） to prepare conductive paper, which, at a low concentration, were better for the formation of conductive networks from conductive sheets. It was found that the Young’s modulus of the conductive paper produced via this strategy reached as high as 7 GPa. Meanwhile, owing to the partial reduction of GO during the polymerization of dopamine, the conductivity of the conductive paper reached as high as 1.3×10-5 S/cm when the PDA-coated GO content was 1 wt%, which was much higher than the conductivity of pure GO （-4.60×10-8 S/cm）. This work provides a new strategy for preparing environmentally friendly conductive papers with good mechanical properties and low conductive fller content, which may be used to produce high-performance, low-cost electronic devices.展开更多
Fog computing in the Internet of Health Things(IoHT)is promising owing to the increasing need for energy-and latency-optimized health sector provisioning.Additionally,clinical data(particularly,medical image data)are ...Fog computing in the Internet of Health Things(IoHT)is promising owing to the increasing need for energy-and latency-optimized health sector provisioning.Additionally,clinical data(particularly,medical image data)are a delicate,highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer needs.Herein,we propose an energy-efficient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud server.The proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize the deterioration of quality between the original and reconstructed(decrypted)images.In this study,the decrypted image quality is preserved by the peak signal-to-noise ratio(PSNR)such that consumers can generate precise medical reports from IoHT devices at the application level.Moreover,a lightweight encryption step is implemented in the fog to improve energy efficiency and reduce additional computations at the cloud server.Experimental results indicate that the TSO-Simon model achieved a high PSNR of 61.37 dB and a pixel change rate of 95.31.展开更多
Medical image analysis is an active research topic,with thousands of studies published in the past few years.Transfer learning(TL)including convolutional neural networks(CNNs)focused to enhance efficiency on an innova...Medical image analysis is an active research topic,with thousands of studies published in the past few years.Transfer learning(TL)including convolutional neural networks(CNNs)focused to enhance efficiency on an innovative task using the knowledge of the same tasks learnt in advance.It has played a major role in medical image analysis since it solves the data scarcity issue along with that it saves hardware resources and time.This study develops an EnhancedTunicate SwarmOptimization withTransfer Learning EnabledMedical Image Analysis System(ETSOTL-MIAS).The goal of the ETSOTL-MIAS technique lies in the identification and classification of diseases through medical imaging.The ETSOTL-MIAS technique involves the Chan Vese segmentation technique to identify the affected regions in the medical image.For feature extraction purposes,the ETSOTL-MIAS technique designs a modified DarkNet-53 model.To avoid the manual hyperparameter adjustment process,the ETSOTLMIAS technique exploits the ETSO algorithm,showing the novelty of the work.Finally,the classification of medical images takes place by random forest(RF)classifier.The performance validation of the ETSOTL-MIAS technique is tested on a benchmark medical image database.The extensive experimental analysis showed the promising performance of the ETSOTL-MIAS technique under different measures.展开更多
The beautiful island of Tobago is the southernmost Caribbean island. The sister island of Trinidad belongs to the Republic of Trinidad and Tobago. Thirty-two species of tunicates were collected from Tobago from depths...The beautiful island of Tobago is the southernmost Caribbean island. The sister island of Trinidad belongs to the Republic of Trinidad and Tobago. Thirty-two species of tunicates were collected from Tobago from depths of 40 m or less and they were listed. Tunicates listed in this work were from collections made in 1956, 1991, 1993, 2002 and 2006 and although specimens were collected from the Atlantic Ocean side of the island and the Caribbean Sea side, all species turned out to be typical Caribbean species.展开更多
文摘A total of 168 macro-zooplankton samples from 42 stations in the central South China Sea （12° ～20° N, 111°～118°E, an area of about 64 × 10^4 km^2 ） were collected in September 1983 （autumn） , April 1984 （spring） , August 1984 （summer） and December 1984 （winter）. Twenty-three species and subspecies of tunicates were found, of which Thalia democratica complex （including T. d. orientalis and T. d. echinata） and Doliolum denticulatum were the dominant species, and accounted for 95.7% , 90. 0%, 91.8% and 90. 5% of the total tunicates found in autumn, winter, spring and summer, respectively. The highest abundance （with a mean of 2.37 ind./m^3 ） occurred in autumn. There are strong correlations between the abundances of the tunicates and those of phytoplankton and chlorophyll a concentration. However, tunicates also aggregate in areas with low primary production in the autumn survey, probably due to the water circulation pattern.
基金supported by the National Key Basic Research Project (2005CB422306)National Natural Science Foundation of China (40876066)
文摘In this paper, the distribution patterns and abundance of pelagic tunicates in the North Yellow Sea of China during the period 2006-2007 were analyzed. Zooplankton samples were obtained with vertical towing from bottom to surface using a WP2 plankton net(200 μm mesh size; mouth area: 0.25 m2). Five species belonging to two classes were identified: Oikopleura dioica, O. longicauda and Fritillaria borealis belonging to class Appendicularia; Salpa fusiformis and Doliolum denticulatum of class Thaliacea. O. dioica and O. longicauda were the dominant species, occurring in the samples of all four seasons, with different distribution patterns. Their maximum abundance were 1664.7 ind. m-3(spring) and 1031.7 ind. m-3(spring) respectively. Following Oikopleura spp. were D. denticulatum, which was found only in autumn with an average abundance of 149.6 ind. m-3, and S. fusiformis, which was detected all the year long except for autumn with low abundance(max. abundance 289.4 ind. m-3 in summer). Only a very small amount of F. borealis was detected in summer samples, with an average abundance of 2.7 ind. m-3. The relationship between tunicates abundances and the environmental factors was analyzed using the stepwise regression model for each species. The variation of appendicularian abundance showed a significant correlation with the surface water temperature and with the concentration of Chl-a. No relationship was found between tunicates abundance and salinity, likely due to the slight changes in surface salinity of the studied area during the four seasons. Salps abundance and that of doliolids were significantly correlated to bottom water temperature, indicating that these two species(S. fusiformis and D. denticulatum) migrate vertically in the water column. In particular D. denticulatum, known to be a warm water species, showed not only an important correlation with water temperature, but also a spatial distribution connected to the warm currents in the North Yellow Sea. The occurrence of D. denticulatum represents an interesting result never found in past research work. Water temperature, algal distribution and currents were the most relevant environmental factors influencing the tunicate abundance and distribution in the North Yellow Sea. Further research is needed in order to get more information on the ecology of these organisms and to better understand their role in the ecosystem including the oceanic food web.
基金the National Natural Science Foundation of China (51373131)Fundamental Research Funds for the Central Universities (XDJK2016A017 and XDJK2016C033)+1 种基金Project of Basic Science and Advanced Technology Research, Chongqing Science and Technology Commission (cstc2016, jcyjA0796)the Talent Project of Southwest University (SWU115034)
文摘Conductive papers made from graphene and its derivatives are important for the development of electronic devices; however, elastomer-based matrices usually make it difficult for the conductive sheets to form continuous conductive networks. In this work, we used tunicate-derived cellulose nanocrystals （TCNC） instead of traditional elastomers as the matrix for polydopamine （PDA）-coated and reduced graphene oxide （GO） to prepare conductive paper, which, at a low concentration, were better for the formation of conductive networks from conductive sheets. It was found that the Young’s modulus of the conductive paper produced via this strategy reached as high as 7 GPa. Meanwhile, owing to the partial reduction of GO during the polymerization of dopamine, the conductivity of the conductive paper reached as high as 1.3×10-5 S/cm when the PDA-coated GO content was 1 wt%, which was much higher than the conductivity of pure GO （-4.60×10-8 S/cm）. This work provides a new strategy for preparing environmentally friendly conductive papers with good mechanical properties and low conductive fller content, which may be used to produce high-performance, low-cost electronic devices.
文摘Fog computing in the Internet of Health Things(IoHT)is promising owing to the increasing need for energy-and latency-optimized health sector provisioning.Additionally,clinical data(particularly,medical image data)are a delicate,highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer needs.Herein,we propose an energy-efficient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud server.The proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize the deterioration of quality between the original and reconstructed(decrypted)images.In this study,the decrypted image quality is preserved by the peak signal-to-noise ratio(PSNR)such that consumers can generate precise medical reports from IoHT devices at the application level.Moreover,a lightweight encryption step is implemented in the fog to improve energy efficiency and reduce additional computations at the cloud server.Experimental results indicate that the TSO-Simon model achieved a high PSNR of 61.37 dB and a pixel change rate of 95.31.
基金support for this work from the Deanship of Scientific Research (DSR),University of Tabuk,Tabuk,Saudi Arabia,under grant number S-1440-0262.
文摘Medical image analysis is an active research topic,with thousands of studies published in the past few years.Transfer learning(TL)including convolutional neural networks(CNNs)focused to enhance efficiency on an innovative task using the knowledge of the same tasks learnt in advance.It has played a major role in medical image analysis since it solves the data scarcity issue along with that it saves hardware resources and time.This study develops an EnhancedTunicate SwarmOptimization withTransfer Learning EnabledMedical Image Analysis System(ETSOTL-MIAS).The goal of the ETSOTL-MIAS technique lies in the identification and classification of diseases through medical imaging.The ETSOTL-MIAS technique involves the Chan Vese segmentation technique to identify the affected regions in the medical image.For feature extraction purposes,the ETSOTL-MIAS technique designs a modified DarkNet-53 model.To avoid the manual hyperparameter adjustment process,the ETSOTLMIAS technique exploits the ETSO algorithm,showing the novelty of the work.Finally,the classification of medical images takes place by random forest(RF)classifier.The performance validation of the ETSOTL-MIAS technique is tested on a benchmark medical image database.The extensive experimental analysis showed the promising performance of the ETSOTL-MIAS technique under different measures.
文摘The beautiful island of Tobago is the southernmost Caribbean island. The sister island of Trinidad belongs to the Republic of Trinidad and Tobago. Thirty-two species of tunicates were collected from Tobago from depths of 40 m or less and they were listed. Tunicates listed in this work were from collections made in 1956, 1991, 1993, 2002 and 2006 and although specimens were collected from the Atlantic Ocean side of the island and the Caribbean Sea side, all species turned out to be typical Caribbean species.
